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  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://githubtocolab.com/CRCTransformers/deepdive-book/blob/main/Chapter-3-TopicModeling.ipynb)"
      ],
      "metadata": {
        "id": "VbtgVnkvUCc4"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "csKhhZMz1M9r"
      },
      "source": [
        "# Motivation"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VZkUezsfUboe"
      },
      "source": [
        "In this chapter, we looked at several applications of the Transformer architecture. In this case study, we see how to use pretrained (or finetuned) Transformer models to do topic modeling. If one is exploring a new dataset, this method could be used during exploratory data analysis.\n",
        "\n",
        "We'll use pretrained Transformers to explore the [Yelp reviews dataset](https://huggingface.co/datasets/yelp_review_full) and see what kinds of things the reviewrs have to say. \n",
        "\n",
        "There are many ways one can generate sentence embeddings, but we are going to use sentence embeddings from the [sentence-transformers](https://github.com/UKPLab/sentence-transformers) library. Sentence-transformers provides models pretrained for specific tasks, such as semantic search. \n",
        "\n",
        "We're going to use [BERTopic](https://github.com/MaartenGr/BERTopic) for topic modeling and [Huggingface Datasets](https://huggingface.co/docs/datasets/) for loading the data. \n",
        "\n",
        "Note: Huggingface Datasets lets you work with large datasets without needing to store the entire thing in memory (the data is memory mapped using Apache Airflow).\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XA9nqXraU_oE"
      },
      "source": [
        "# Environment setup"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OL2Ozsq-USWV",
        "outputId": "d284219b-8879-4e21-bd79-85ca5981143b"
      },
      "source": [
        "!pip install -U datasets==2.2.1 bertopic==0.10.0"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: datasets==2.2.1 in /usr/local/lib/python3.7/dist-packages (2.2.1)\n",
            "Collecting bertopic==0.10.0\n",
            "  Downloading bertopic-0.10.0-py2.py3-none-any.whl (58 kB)\n",
            "\u001b[K     |████████████████████████████████| 58 kB 2.6 MB/s \n",
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            "Requirement already satisfied: umap-learn>=0.5.0 in /usr/local/lib/python3.7/dist-packages (from bertopic==0.10.0) (0.5.3)\n",
            "Requirement already satisfied: plotly>=4.7.0 in /usr/local/lib/python3.7/dist-packages (from bertopic==0.10.0) (4.14.2)\n",
            "Requirement already satisfied: sentence-transformers>=0.4.1 in /usr/local/lib/python3.7/dist-packages (from bertopic==0.10.0) (2.2.0)\n",
            "Requirement already satisfied: hdbscan>=0.8.28 in /usr/local/lib/python3.7/dist-packages (from bertopic==0.10.0) (0.8.28)\n",
            "Collecting pyyaml<6.0\n",
            "  Downloading PyYAML-5.4.1-cp37-cp37m-manylinux1_x86_64.whl (636 kB)\n",
            "\u001b[K     |████████████████████████████████| 636 kB 9.8 MB/s \n",
            "\u001b[?25hRequirement already satisfied: scipy>=1.0 in /usr/local/lib/python3.7/dist-packages (from hdbscan>=0.8.28->bertopic==0.10.0) (1.4.1)\n",
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            "Requirement already satisfied: transformers<5.0.0,>=4.6.0 in /usr/local/lib/python3.7/dist-packages (from sentence-transformers>=0.4.1->bertopic==0.10.0) (4.12.2)\n",
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            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.7/dist-packages (from transformers<5.0.0,>=4.6.0->sentence-transformers>=0.4.1->bertopic==0.10.0) (2019.12.20)\n",
            "Requirement already satisfied: tokenizers<0.11,>=0.10.1 in /usr/local/lib/python3.7/dist-packages (from transformers<5.0.0,>=4.6.0->sentence-transformers>=0.4.1->bertopic==0.10.0) (0.10.3)\n",
            "Requirement already satisfied: pynndescent>=0.5 in /usr/local/lib/python3.7/dist-packages (from umap-learn>=0.5.0->bertopic==0.10.0) (0.5.7)\n",
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            "Requirement already satisfied: setuptools in /usr/local/lib/python3.7/dist-packages (from numba>=0.49->umap-learn>=0.5.0->bertopic==0.10.0) (57.4.0)\n",
            "Requirement already satisfied: llvmlite<0.35,>=0.34.0.dev0 in /usr/local/lib/python3.7/dist-packages (from numba>=0.49->umap-learn>=0.5.0->bertopic==0.10.0) (0.34.0)\n",
            "Requirement already satisfied: asynctest==0.13.0 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets==2.2.1) (0.13.0)\n",
            "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets==2.2.1) (1.2.0)\n",
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            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets==2.2.1) (1.3.0)\n",
            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets==2.2.1) (6.0.2)\n",
            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets==2.2.1) (21.4.0)\n",
            "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.7/dist-packages (from aiohttp->datasets==2.2.1) (4.0.2)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata->datasets==2.2.1) (3.8.0)\n",
            "Requirement already satisfied: click in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers<5.0.0,>=4.6.0->sentence-transformers>=0.4.1->bertopic==0.10.0) (7.1.2)\n",
            "Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /usr/local/lib/python3.7/dist-packages (from torchvision->sentence-transformers>=0.4.1->bertopic==0.10.0) (7.1.2)\n",
            "Installing collected packages: pyyaml, bertopic\n",
            "  Attempting uninstall: pyyaml\n",
            "    Found existing installation: PyYAML 6.0\n",
            "    Uninstalling PyYAML-6.0:\n",
            "      Successfully uninstalled PyYAML-6.0\n",
            "  Attempting uninstall: bertopic\n",
            "    Found existing installation: bertopic 0.9.1\n",
            "    Uninstalling bertopic-0.9.1:\n",
            "      Successfully uninstalled bertopic-0.9.1\n",
            "Successfully installed bertopic-0.10.0 pyyaml-5.4.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IofruY0zsr56"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "%matplotlib notebook"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Qjes2CL702Tp"
      },
      "source": [
        "# Data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LT3FdbCiVXR1"
      },
      "source": [
        "from datasets import load_dataset\n",
        "import numpy as np"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HDsV-UwuAamv"
      },
      "source": [
        "There are 650,000 reviews in the dataset. To keep the runtime of this case study within reason, we'll only process the first 10,000 reviews. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5Qc3WLc-A5z6"
      },
      "source": [
        "To process more reviews, simply change `N`."
      ]
    },
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        "outputId": "351fed50-77b3-4eef-a15e-a0e6e3e49a43"
      },
      "source": [
        "N = 10_000\n",
        "dataset = load_dataset(\"yelp_review_full\", split=f\"train[:{N}]\")"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading builder script:   0%|          | 0.00/1.80k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "af90aa84b3c545319a2871d1a3d84e5e"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "cc05e5205ab94eb899b02cc65f0af876"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading and preparing dataset yelp_review_full/yelp_review_full (download: 187.06 MiB, generated: 496.94 MiB, post-processed: Unknown size, total: 684.00 MiB) to /root/.cache/huggingface/datasets/yelp_review_full/yelp_review_full/1.0.0/e8e18e19d7be9e75642fc66b198abadb116f73599ec89a69ba5dd8d1e57ba0bf...\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "36d7457231224d8b8a3cee9f779564e2"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Generating train split:   0%|          | 0/650000 [00:00<?, ? examples/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "27416cabac5a4120a617881564f183a6"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "a99709595736418bbdb971f5abc90e1b"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dataset yelp_review_full downloaded and prepared to /root/.cache/huggingface/datasets/yelp_review_full/yelp_review_full/1.0.0/e8e18e19d7be9e75642fc66b198abadb116f73599ec89a69ba5dd8d1e57ba0bf. Subsequent calls will reuse this data.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "zCPuKvek7bX0",
        "outputId": "5763188d-c93f-4060-a551-3724db8260dd"
      },
      "source": [
        "dataset"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Dataset({\n",
              "    features: ['label', 'text'],\n",
              "    num_rows: 10000\n",
              "})"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uRKWk33a1pSy"
      },
      "source": [
        "# Sentence Embeddings\n",
        "\n",
        "In this case study, we're interested in exploring the Yelp dataset, seeing what topics are being written about.\n",
        "\n",
        "We'll use the [all-mpnet-base-v2](https://huggingface.co/sentence-transformers/all-mpnet-base-v2) model from sentence-transformers. It's built to perform well on semantic search when embedding sentences and longer spans of text."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eig1WkHa_VfL"
      },
      "source": [
        "To use the GPU when computing the embeddings, we set the `device` parameter in `SentenceTransformer` to \"cuda\"."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "C_KrFaseDNPO",
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          ]
        },
        "outputId": "4df662a4-afd9-4094-89a8-b193975c39c9"
      },
      "source": [
        "from sentence_transformers import SentenceTransformer\n",
        "\n",
        "embeddings_model = SentenceTransformer(\"all-mpnet-base-v2\", device=\"cuda\")"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
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        {
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    {
      "cell_type": "code",
      "metadata": {
        "id": "Kq7JMl8GECzy"
      },
      "source": [
        "# We embed the reviews in batches, to speed things up\n",
        "batch_size = 256"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4lvthRe_D2X4"
      },
      "source": [
        "def embed(batch):\n",
        "    batch[\"embedding\"] = embeddings_model.encode(batch[\"text\"])\n",
        "    return batch"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
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            "6bfcaec6aee54901b1f09e0c17a00306",
            "1fa11a5a464745a28dc1d237772b3535",
            "dda73cf060f1442695db2af1394741f7",
            "30fb1245a5d247829a6f7554e5c38233",
            "20d217960d87410cbac641f608d6010d",
            "6749531097e24d05a4647bb7222574b4",
            "cbb9cd743d6249c09a41faa1263edfc0",
            "25b9b6655341464896668b1352eddf21",
            "1c29c803613d45deb3d76b655afdcab4"
          ]
        },
        "id": "rJG9H2iTDdYh",
        "outputId": "09cd707a-c751-4960-d319-45a8103be5b2"
      },
      "source": [
        "dataset = dataset.map(embed, batch_size=batch_size, batched=True)\n",
        "dataset.set_format(type='numpy', columns=['embedding'], output_all_columns=True)"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Parameter 'function'=<function embed at 0x7fa40f3b78c0> of the transform datasets.arrow_dataset.Dataset._map_single couldn't be hashed properly, a random hash was used instead. Make sure your transforms and parameters are serializable with pickle or dill for the dataset fingerprinting and caching to work. If you reuse this transform, the caching mechanism will consider it to be different from the previous calls and recompute everything. This warning is only showed once. Subsequent hashing failures won't be showed.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/40 [00:00<?, ?ba/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "c488998d791547bc981379135e0b56e4"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dBQVrSFq0iLJ"
      },
      "source": [
        "# Topics"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "u_WBhwSFUa4_"
      },
      "source": [
        "## Building Topics"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "t2KdImj8-kuH"
      },
      "source": [
        "from bertopic import BERTopic"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XB8IXUEwYv3R"
      },
      "source": [
        "topic_model = BERTopic(n_gram_range=(1, 2))"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lLIuiPvOi73E",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c77066e5-2785-43df-b49e-52e95a4bddd3"
      },
      "source": [
        "topics, probs = topic_model.fit_transform(dataset[\"text\"], \n",
        "                                          np.array(dataset[\"embedding\"]))"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/numba/np/ufunc/parallel.py:363: NumbaWarning: The TBB threading layer requires TBB version 2019.5 or later i.e., TBB_INTERFACE_VERSION >= 11005. Found TBB_INTERFACE_VERSION = 9107. The TBB threading layer is disabled.\n",
            "  warnings.warn(problem)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8q6c7WuXr4oG"
      },
      "source": [
        "topic_model1 = BERTopic(n_gram_range=(1, 3), calculate_probabilities=True)\n",
        "topics1, probs1 = topic_model1.fit_transform(dataset[\"text\"], \n",
        "                                          np.array(dataset[\"embedding\"]))"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wheoH_eLVVOF",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "dca4ca3f-5adf-4453-ae74-c24d28f3ed49"
      },
      "source": [
        "print(f\"Number of topics: {len(topic_model.get_topics())}\")"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Number of topics: 139\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fD9Rq83U6agq"
      },
      "source": [
        "Now that we have computed a topic distribution, we need to see what kind of reviews are in each topic."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nAUHMKSFGk0M",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "3f3a4fb1-58fa-41e7-ed26-729503bc4a3a"
      },
      "source": [
        "topic_model.get_topic_info()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Topic  Count                                        Name\n",
              "0       -1   3115                           -1_the_and_was_to\n",
              "1        0    368                             0_we_our_to_was\n",
              "2        1    340                     1_italian_pasta_was_the\n",
              "3        2    272              2_pizza_the pizza_crust_cheese\n",
              "4        3    244         3_chinese_chinese food_chicken_food\n",
              "..     ...    ...                                         ...\n",
              "134    133     12     133_comic_comics_comic book_comic books\n",
              "135    134     11            134_thai_pad_pad thai_thai house\n",
              "136    135     11                          135_we_us_were_was\n",
              "137    136     11              136_yum_yum yum_salad_julianas\n",
              "138    137     10  137_showmars_pita_love showmars_salad pita\n",
              "\n",
              "[139 rows x 3 columns]"
            ],
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              "          document.querySelector('#df-5f763467-913f-483d-85a9-71b5ba894cac button.colab-df-convert');\n",
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              "          const element = document.querySelector('#df-5f763467-913f-483d-85a9-71b5ba894cac');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
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              "  "
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MqMI8QNNo6td"
      },
      "source": [
        "## Topic size distribution"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "jX0HGRQdHzUj"
      },
      "source": [
        "What is the distribution of topic size, where the size is the number of reviews that contain that topic?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1MjO_8uEo-LS"
      },
      "source": [
        "topic_sizes = topic_model.get_topic_freq()"
      ],
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xlaYLrx5IPb6",
        "colab": {
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          "height": 424
        },
        "outputId": "a3c2fca2-001b-466f-fe3a-115b7959d31e"
      },
      "source": [
        "topic_sizes"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Topic  Count\n",
              "0       -1   3115\n",
              "1        0    368\n",
              "2        1    340\n",
              "3        2    272\n",
              "4        3    244\n",
              "..     ...    ...\n",
              "134    133     12\n",
              "135    134     11\n",
              "136    135     11\n",
              "137    136     11\n",
              "138    137     10\n",
              "\n",
              "[139 rows x 2 columns]"
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              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-8dad3547-f19f-44f4-b3f8-fdfab0831b5a');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dpFfXFNUGqHv"
      },
      "source": [
        "Note the topic with id of -1. This corresponds to the unassigned cluster output by the HDBSCAN algorithm. The unassigned cluster is composed of all the things that could not be assigned to one of the other clusters. It can *generally* be ignored, but if it were too large, it would be a sign that our choice of parameters are probably not good for our data."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SO5J-zH0sDXj",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "27733c30-dcbe-4ff2-bafb-9e83100d06a2"
      },
      "source": [
        "topic_sizes[topic_sizes[\"Topic\"] != -1][\"Count\"].hist()"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Javascript object>"
            ],
            "application/javascript": [
              "/* Put everything inside the global mpl namespace */\n",
              "window.mpl = {};\n",
              "\n",
              "\n",
              "mpl.get_websocket_type = function() {\n",
              "    if (typeof(WebSocket) !== 'undefined') {\n",
              "        return WebSocket;\n",
              "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
              "        return MozWebSocket;\n",
              "    } else {\n",
              "        alert('Your browser does not have WebSocket support. ' +\n",
              "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
              "              'Firefox 4 and 5 are also supported but you ' +\n",
              "              'have to enable WebSockets in about:config.');\n",
              "    };\n",
              "}\n",
              "\n",
              "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
              "    this.id = figure_id;\n",
              "\n",
              "    this.ws = websocket;\n",
              "\n",
              "    this.supports_binary = (this.ws.binaryType != undefined);\n",
              "\n",
              "    if (!this.supports_binary) {\n",
              "        var warnings = document.getElementById(\"mpl-warnings\");\n",
              "        if (warnings) {\n",
              "            warnings.style.display = 'block';\n",
              "            warnings.textContent = (\n",
              "                \"This browser does not support binary websocket messages. \" +\n",
              "                    \"Performance may be slow.\");\n",
              "        }\n",
              "    }\n",
              "\n",
              "    this.imageObj = new Image();\n",
              "\n",
              "    this.context = undefined;\n",
              "    this.message = undefined;\n",
              "    this.canvas = undefined;\n",
              "    this.rubberband_canvas = undefined;\n",
              "    this.rubberband_context = undefined;\n",
              "    this.format_dropdown = undefined;\n",
              "\n",
              "    this.image_mode = 'full';\n",
              "\n",
              "    this.root = $('<div/>');\n",
              "    this._root_extra_style(this.root)\n",
              "    this.root.attr('style', 'display: inline-block');\n",
              "\n",
              "    $(parent_element).append(this.root);\n",
              "\n",
              "    this._init_header(this);\n",
              "    this._init_canvas(this);\n",
              "    this._init_toolbar(this);\n",
              "\n",
              "    var fig = this;\n",
              "\n",
              "    this.waiting = false;\n",
              "\n",
              "    this.ws.onopen =  function () {\n",
              "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
              "            fig.send_message(\"send_image_mode\", {});\n",
              "            if (mpl.ratio != 1) {\n",
              "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
              "            }\n",
              "            fig.send_message(\"refresh\", {});\n",
              "        }\n",
              "\n",
              "    this.imageObj.onload = function() {\n",
              "            if (fig.image_mode == 'full') {\n",
              "                // Full images could contain transparency (where diff images\n",
              "                // almost always do), so we need to clear the canvas so that\n",
              "                // there is no ghosting.\n",
              "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
              "            }\n",
              "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
              "        };\n",
              "\n",
              "    this.imageObj.onunload = function() {\n",
              "        fig.ws.close();\n",
              "    }\n",
              "\n",
              "    this.ws.onmessage = this._make_on_message_function(this);\n",
              "\n",
              "    this.ondownload = ondownload;\n",
              "}\n",
              "\n",
              "mpl.figure.prototype._init_header = function() {\n",
              "    var titlebar = $(\n",
              "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
              "        'ui-helper-clearfix\"/>');\n",
              "    var titletext = $(\n",
              "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
              "        'text-align: center; padding: 3px;\"/>');\n",
              "    titlebar.append(titletext)\n",
              "    this.root.append(titlebar);\n",
              "    this.header = titletext[0];\n",
              "}\n",
              "\n",
              "\n",
              "\n",
              "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
              "\n",
              "}\n",
              "\n",
              "\n",
              "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
              "\n",
              "}\n",
              "\n",
              "mpl.figure.prototype._init_canvas = function() {\n",
              "    var fig = this;\n",
              "\n",
              "    var canvas_div = $('<div/>');\n",
              "\n",
              "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
              "\n",
              "    function canvas_keyboard_event(event) {\n",
              "        return fig.key_event(event, event['data']);\n",
              "    }\n",
              "\n",
              "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
              "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
              "    this.canvas_div = canvas_div\n",
              "    this._canvas_extra_style(canvas_div)\n",
              "    this.root.append(canvas_div);\n",
              "\n",
              "    var canvas = $('<canvas/>');\n",
              "    canvas.addClass('mpl-canvas');\n",
              "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
              "\n",
              "    this.canvas = canvas[0];\n",
              "    this.context = canvas[0].getContext(\"2d\");\n",
              "\n",
              "    var backingStore = this.context.backingStorePixelRatio ||\n",
              "\tthis.context.webkitBackingStorePixelRatio ||\n",
              "\tthis.context.mozBackingStorePixelRatio ||\n",
              "\tthis.context.msBackingStorePixelRatio ||\n",
              "\tthis.context.oBackingStorePixelRatio ||\n",
              "\tthis.context.backingStorePixelRatio || 1;\n",
              "\n",
              "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
              "\n",
              "    var rubberband = $('<canvas/>');\n",
              "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
              "\n",
              "    var pass_mouse_events = true;\n",
              "\n",
              "    canvas_div.resizable({\n",
              "        start: function(event, ui) {\n",
              "            pass_mouse_events = false;\n",
              "        },\n",
              "        resize: function(event, ui) {\n",
              "            fig.request_resize(ui.size.width, ui.size.height);\n",
              "        },\n",
              "        stop: function(event, ui) {\n",
              "            pass_mouse_events = true;\n",
              "            fig.request_resize(ui.size.width, ui.size.height);\n",
              "        },\n",
              "    });\n",
              "\n",
              "    function mouse_event_fn(event) {\n",
              "        if (pass_mouse_events)\n",
              "            return fig.mouse_event(event, event['data']);\n",
              "    }\n",
              "\n",
              "    rubberband.mousedown('button_press', mouse_event_fn);\n",
              "    rubberband.mouseup('button_release', mouse_event_fn);\n",
              "    // Throttle sequential mouse events to 1 every 20ms.\n",
              "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
              "\n",
              "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
              "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
              "\n",
              "    canvas_div.on(\"wheel\", function (event) {\n",
              "        event = event.originalEvent;\n",
              "        event['data'] = 'scroll'\n",
              "        if (event.deltaY < 0) {\n",
              "            event.step = 1;\n",
              "        } else {\n",
              "            event.step = -1;\n",
              "        }\n",
              "        mouse_event_fn(event);\n",
              "    });\n",
              "\n",
              "    canvas_div.append(canvas);\n",
              "    canvas_div.append(rubberband);\n",
              "\n",
              "    this.rubberband = rubberband;\n",
              "    this.rubberband_canvas = rubberband[0];\n",
              "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
              "    this.rubberband_context.strokeStyle = \"#000000\";\n",
              "\n",
              "    this._resize_canvas = function(width, height) {\n",
              "        // Keep the size of the canvas, canvas container, and rubber band\n",
              "        // canvas in synch.\n",
              "        canvas_div.css('width', width)\n",
              "        canvas_div.css('height', height)\n",
              "\n",
              "        canvas.attr('width', width * mpl.ratio);\n",
              "        canvas.attr('height', height * mpl.ratio);\n",
              "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
              "\n",
              "        rubberband.attr('width', width);\n",
              "        rubberband.attr('height', height);\n",
              "    }\n",
              "\n",
              "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
              "    // upon first draw.\n",
              "    this._resize_canvas(600, 600);\n",
              "\n",
              "    // Disable right mouse context menu.\n",
              "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
              "        return false;\n",
              "    });\n",
              "\n",
              "    function set_focus () {\n",
              "        canvas.focus();\n",
              "        canvas_div.focus();\n",
              "    }\n",
              "\n",
              "    window.setTimeout(set_focus, 100);\n",
              "}\n",
              "\n",
              "mpl.figure.prototype._init_toolbar = function() {\n",
              "    var fig = this;\n",
              "\n",
              "    var nav_element = $('<div/>');\n",
              "    nav_element.attr('style', 'width: 100%');\n",
              "    this.root.append(nav_element);\n",
              "\n",
              "    // Define a callback function for later on.\n",
              "    function toolbar_event(event) {\n",
              "        return fig.toolbar_button_onclick(event['data']);\n",
              "    }\n",
              "    function toolbar_mouse_event(event) {\n",
              "        return fig.toolbar_button_onmouseover(event['data']);\n",
              "    }\n",
              "\n",
              "    for(var toolbar_ind in mpl.toolbar_items) {\n",
              "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
              "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
              "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
              "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
              "\n",
              "        if (!name) {\n",
              "            // put a spacer in here.\n",
              "            continue;\n",
              "        }\n",
              "        var button = $('<button/>');\n",
              "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
              "                        'ui-button-icon-only');\n",
              "        button.attr('role', 'button');\n",
              "        button.attr('aria-disabled', 'false');\n",
              "        button.click(method_name, toolbar_event);\n",
              "        button.mouseover(tooltip, toolbar_mouse_event);\n",
              "\n",
              "        var icon_img = $('<span/>');\n",
              "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
              "        icon_img.addClass(image);\n",
              "        icon_img.addClass('ui-corner-all');\n",
              "\n",
              "        var tooltip_span = $('<span/>');\n",
              "        tooltip_span.addClass('ui-button-text');\n",
              "        tooltip_span.html(tooltip);\n",
              "\n",
              "        button.append(icon_img);\n",
              "        button.append(tooltip_span);\n",
              "\n",
              "        nav_element.append(button);\n",
              "    }\n",
              "\n",
              "    var fmt_picker_span = $('<span/>');\n",
              "\n",
              "    var fmt_picker = $('<select/>');\n",
              "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
              "    fmt_picker_span.append(fmt_picker);\n",
              "    nav_element.append(fmt_picker_span);\n",
              "    this.format_dropdown = fmt_picker[0];\n",
              "\n",
              "    for (var ind in mpl.extensions) {\n",
              "        var fmt = mpl.extensions[ind];\n",
              "        var option = $(\n",
              "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
              "        fmt_picker.append(option);\n",
              "    }\n",
              "\n",
              "    // Add hover states to the ui-buttons\n",
              "    $( \".ui-button\" ).hover(\n",
              "        function() { $(this).addClass(\"ui-state-hover\");},\n",
              "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
              "    );\n",
              "\n",
              "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
              "    nav_element.append(status_bar);\n",
              "    this.message = status_bar[0];\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
              "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
              "    // which will in turn request a refresh of the image.\n",
              "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.send_message = function(type, properties) {\n",
              "    properties['type'] = type;\n",
              "    properties['figure_id'] = this.id;\n",
              "    this.ws.send(JSON.stringify(properties));\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.send_draw_message = function() {\n",
              "    if (!this.waiting) {\n",
              "        this.waiting = true;\n",
              "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
              "    }\n",
              "}\n",
              "\n",
              "\n",
              "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
              "    var format_dropdown = fig.format_dropdown;\n",
              "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
              "    fig.ondownload(fig, format);\n",
              "}\n",
              "\n",
              "\n",
              "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
              "    var size = msg['size'];\n",
              "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
              "        fig._resize_canvas(size[0], size[1]);\n",
              "        fig.send_message(\"refresh\", {});\n",
              "    };\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
              "    var x0 = msg['x0'] / mpl.ratio;\n",
              "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
              "    var x1 = msg['x1'] / mpl.ratio;\n",
              "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
              "    x0 = Math.floor(x0) + 0.5;\n",
              "    y0 = Math.floor(y0) + 0.5;\n",
              "    x1 = Math.floor(x1) + 0.5;\n",
              "    y1 = Math.floor(y1) + 0.5;\n",
              "    var min_x = Math.min(x0, x1);\n",
              "    var min_y = Math.min(y0, y1);\n",
              "    var width = Math.abs(x1 - x0);\n",
              "    var height = Math.abs(y1 - y0);\n",
              "\n",
              "    fig.rubberband_context.clearRect(\n",
              "        0, 0, fig.canvas.width / mpl.ratio, fig.canvas.height / mpl.ratio);\n",
              "\n",
              "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
              "    // Updates the figure title.\n",
              "    fig.header.textContent = msg['label'];\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
              "    var cursor = msg['cursor'];\n",
              "    switch(cursor)\n",
              "    {\n",
              "    case 0:\n",
              "        cursor = 'pointer';\n",
              "        break;\n",
              "    case 1:\n",
              "        cursor = 'default';\n",
              "        break;\n",
              "    case 2:\n",
              "        cursor = 'crosshair';\n",
              "        break;\n",
              "    case 3:\n",
              "        cursor = 'move';\n",
              "        break;\n",
              "    }\n",
              "    fig.rubberband_canvas.style.cursor = cursor;\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
              "    fig.message.textContent = msg['message'];\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
              "    // Request the server to send over a new figure.\n",
              "    fig.send_draw_message();\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
              "    fig.image_mode = msg['mode'];\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.updated_canvas_event = function() {\n",
              "    // Called whenever the canvas gets updated.\n",
              "    this.send_message(\"ack\", {});\n",
              "}\n",
              "\n",
              "// A function to construct a web socket function for onmessage handling.\n",
              "// Called in the figure constructor.\n",
              "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
              "    return function socket_on_message(evt) {\n",
              "        if (evt.data instanceof Blob) {\n",
              "            /* FIXME: We get \"Resource interpreted as Image but\n",
              "             * transferred with MIME type text/plain:\" errors on\n",
              "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
              "             * to be part of the websocket stream */\n",
              "            evt.data.type = \"image/png\";\n",
              "\n",
              "            /* Free the memory for the previous frames */\n",
              "            if (fig.imageObj.src) {\n",
              "                (window.URL || window.webkitURL).revokeObjectURL(\n",
              "                    fig.imageObj.src);\n",
              "            }\n",
              "\n",
              "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
              "                evt.data);\n",
              "            fig.updated_canvas_event();\n",
              "            fig.waiting = false;\n",
              "            return;\n",
              "        }\n",
              "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
              "            fig.imageObj.src = evt.data;\n",
              "            fig.updated_canvas_event();\n",
              "            fig.waiting = false;\n",
              "            return;\n",
              "        }\n",
              "\n",
              "        var msg = JSON.parse(evt.data);\n",
              "        var msg_type = msg['type'];\n",
              "\n",
              "        // Call the  \"handle_{type}\" callback, which takes\n",
              "        // the figure and JSON message as its only arguments.\n",
              "        try {\n",
              "            var callback = fig[\"handle_\" + msg_type];\n",
              "        } catch (e) {\n",
              "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
              "            return;\n",
              "        }\n",
              "\n",
              "        if (callback) {\n",
              "            try {\n",
              "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
              "                callback(fig, msg);\n",
              "            } catch (e) {\n",
              "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
              "            }\n",
              "        }\n",
              "    };\n",
              "}\n",
              "\n",
              "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
              "mpl.findpos = function(e) {\n",
              "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
              "    var targ;\n",
              "    if (!e)\n",
              "        e = window.event;\n",
              "    if (e.target)\n",
              "        targ = e.target;\n",
              "    else if (e.srcElement)\n",
              "        targ = e.srcElement;\n",
              "    if (targ.nodeType == 3) // defeat Safari bug\n",
              "        targ = targ.parentNode;\n",
              "\n",
              "    // jQuery normalizes the pageX and pageY\n",
              "    // pageX,Y are the mouse positions relative to the document\n",
              "    // offset() returns the position of the element relative to the document\n",
              "    var x = e.pageX - $(targ).offset().left;\n",
              "    var y = e.pageY - $(targ).offset().top;\n",
              "\n",
              "    return {\"x\": x, \"y\": y};\n",
              "};\n",
              "\n",
              "/*\n",
              " * return a copy of an object with only non-object keys\n",
              " * we need this to avoid circular references\n",
              " * http://stackoverflow.com/a/24161582/3208463\n",
              " */\n",
              "function simpleKeys (original) {\n",
              "  return Object.keys(original).reduce(function (obj, key) {\n",
              "    if (typeof original[key] !== 'object')\n",
              "        obj[key] = original[key]\n",
              "    return obj;\n",
              "  }, {});\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.mouse_event = function(event, name) {\n",
              "    var canvas_pos = mpl.findpos(event)\n",
              "\n",
              "    if (name === 'button_press')\n",
              "    {\n",
              "        this.canvas.focus();\n",
              "        this.canvas_div.focus();\n",
              "    }\n",
              "\n",
              "    var x = canvas_pos.x * mpl.ratio;\n",
              "    var y = canvas_pos.y * mpl.ratio;\n",
              "\n",
              "    this.send_message(name, {x: x, y: y, button: event.button,\n",
              "                             step: event.step,\n",
              "                             guiEvent: simpleKeys(event)});\n",
              "\n",
              "    /* This prevents the web browser from automatically changing to\n",
              "     * the text insertion cursor when the button is pressed.  We want\n",
              "     * to control all of the cursor setting manually through the\n",
              "     * 'cursor' event from matplotlib */\n",
              "    event.preventDefault();\n",
              "    return false;\n",
              "}\n",
              "\n",
              "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
              "    // Handle any extra behaviour associated with a key event\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.key_event = function(event, name) {\n",
              "\n",
              "    // Prevent repeat events\n",
              "    if (name == 'key_press')\n",
              "    {\n",
              "        if (event.which === this._key)\n",
              "            return;\n",
              "        else\n",
              "            this._key = event.which;\n",
              "    }\n",
              "    if (name == 'key_release')\n",
              "        this._key = null;\n",
              "\n",
              "    var value = '';\n",
              "    if (event.ctrlKey && event.which != 17)\n",
              "        value += \"ctrl+\";\n",
              "    if (event.altKey && event.which != 18)\n",
              "        value += \"alt+\";\n",
              "    if (event.shiftKey && event.which != 16)\n",
              "        value += \"shift+\";\n",
              "\n",
              "    value += 'k';\n",
              "    value += event.which.toString();\n",
              "\n",
              "    this._key_event_extra(event, name);\n",
              "\n",
              "    this.send_message(name, {key: value,\n",
              "                             guiEvent: simpleKeys(event)});\n",
              "    return false;\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
              "    if (name == 'download') {\n",
              "        this.handle_save(this, null);\n",
              "    } else {\n",
              "        this.send_message(\"toolbar_button\", {name: name});\n",
              "    }\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
              "    this.message.textContent = tooltip;\n",
              "};\n",
              "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
              "\n",
              "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
              "\n",
              "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
              "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
              "    // object with the appropriate methods. Currently this is a non binary\n",
              "    // socket, so there is still some room for performance tuning.\n",
              "    var ws = {};\n",
              "\n",
              "    ws.close = function() {\n",
              "        comm.close()\n",
              "    };\n",
              "    ws.send = function(m) {\n",
              "        //console.log('sending', m);\n",
              "        comm.send(m);\n",
              "    };\n",
              "    // Register the callback with on_msg.\n",
              "    comm.on_msg(function(msg) {\n",
              "        //console.log('receiving', msg['content']['data'], msg);\n",
              "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
              "        ws.onmessage(msg['content']['data'])\n",
              "    });\n",
              "    return ws;\n",
              "}\n",
              "\n",
              "mpl.mpl_figure_comm = function(comm, msg) {\n",
              "    // This is the function which gets called when the mpl process\n",
              "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
              "\n",
              "    var id = msg.content.data.id;\n",
              "    // Get hold of the div created by the display call when the Comm\n",
              "    // socket was opened in Python.\n",
              "    var element = $(\"#\" + id);\n",
              "    var ws_proxy = comm_websocket_adapter(comm)\n",
              "\n",
              "    function ondownload(figure, format) {\n",
              "        window.open(figure.imageObj.src);\n",
              "    }\n",
              "\n",
              "    var fig = new mpl.figure(id, ws_proxy,\n",
              "                           ondownload,\n",
              "                           element.get(0));\n",
              "\n",
              "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
              "    // web socket which is closed, not our websocket->open comm proxy.\n",
              "    ws_proxy.onopen();\n",
              "\n",
              "    fig.parent_element = element.get(0);\n",
              "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
              "    if (!fig.cell_info) {\n",
              "        console.error(\"Failed to find cell for figure\", id, fig);\n",
              "        return;\n",
              "    }\n",
              "\n",
              "    var output_index = fig.cell_info[2]\n",
              "    var cell = fig.cell_info[0];\n",
              "\n",
              "};\n",
              "\n",
              "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
              "    var width = fig.canvas.width/mpl.ratio\n",
              "    fig.root.unbind('remove')\n",
              "\n",
              "    // Update the output cell to use the data from the current canvas.\n",
              "    fig.push_to_output();\n",
              "    var dataURL = fig.canvas.toDataURL();\n",
              "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
              "    // the notebook keyboard shortcuts fail.\n",
              "    IPython.keyboard_manager.enable()\n",
              "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
              "    fig.close_ws(fig, msg);\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.close_ws = function(fig, msg){\n",
              "    fig.send_message('closing', msg);\n",
              "    // fig.ws.close()\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
              "    // Turn the data on the canvas into data in the output cell.\n",
              "    var width = this.canvas.width/mpl.ratio\n",
              "    var dataURL = this.canvas.toDataURL();\n",
              "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.updated_canvas_event = function() {\n",
              "    // Tell IPython that the notebook contents must change.\n",
              "    IPython.notebook.set_dirty(true);\n",
              "    this.send_message(\"ack\", {});\n",
              "    var fig = this;\n",
              "    // Wait a second, then push the new image to the DOM so\n",
              "    // that it is saved nicely (might be nice to debounce this).\n",
              "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
              "}\n",
              "\n",
              "mpl.figure.prototype._init_toolbar = function() {\n",
              "    var fig = this;\n",
              "\n",
              "    var nav_element = $('<div/>');\n",
              "    nav_element.attr('style', 'width: 100%');\n",
              "    this.root.append(nav_element);\n",
              "\n",
              "    // Define a callback function for later on.\n",
              "    function toolbar_event(event) {\n",
              "        return fig.toolbar_button_onclick(event['data']);\n",
              "    }\n",
              "    function toolbar_mouse_event(event) {\n",
              "        return fig.toolbar_button_onmouseover(event['data']);\n",
              "    }\n",
              "\n",
              "    for(var toolbar_ind in mpl.toolbar_items){\n",
              "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
              "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
              "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
              "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
              "\n",
              "        if (!name) { continue; };\n",
              "\n",
              "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
              "        button.click(method_name, toolbar_event);\n",
              "        button.mouseover(tooltip, toolbar_mouse_event);\n",
              "        nav_element.append(button);\n",
              "    }\n",
              "\n",
              "    // Add the status bar.\n",
              "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
              "    nav_element.append(status_bar);\n",
              "    this.message = status_bar[0];\n",
              "\n",
              "    // Add the close button to the window.\n",
              "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
              "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
              "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
              "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
              "    buttongrp.append(button);\n",
              "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
              "    titlebar.prepend(buttongrp);\n",
              "}\n",
              "\n",
              "mpl.figure.prototype._root_extra_style = function(el){\n",
              "    var fig = this\n",
              "    el.on(\"remove\", function(){\n",
              "\tfig.close_ws(fig, {});\n",
              "    });\n",
              "}\n",
              "\n",
              "mpl.figure.prototype._canvas_extra_style = function(el){\n",
              "    // this is important to make the div 'focusable\n",
              "    el.attr('tabindex', 0)\n",
              "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
              "    // off when our div gets focus\n",
              "\n",
              "    // location in version 3\n",
              "    if (IPython.notebook.keyboard_manager) {\n",
              "        IPython.notebook.keyboard_manager.register_events(el);\n",
              "    }\n",
              "    else {\n",
              "        // location in version 2\n",
              "        IPython.keyboard_manager.register_events(el);\n",
              "    }\n",
              "\n",
              "}\n",
              "\n",
              "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
              "    var manager = IPython.notebook.keyboard_manager;\n",
              "    if (!manager)\n",
              "        manager = IPython.keyboard_manager;\n",
              "\n",
              "    // Check for shift+enter\n",
              "    if (event.shiftKey && event.which == 13) {\n",
              "        this.canvas_div.blur();\n",
              "        // select the cell after this one\n",
              "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
              "        IPython.notebook.select(index + 1);\n",
              "    }\n",
              "}\n",
              "\n",
              "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
              "    fig.ondownload(fig, null);\n",
              "}\n",
              "\n",
              "\n",
              "mpl.find_output_cell = function(html_output) {\n",
              "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
              "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
              "    // IPython event is triggered only after the cells have been serialised, which for\n",
              "    // our purposes (turning an active figure into a static one), is too late.\n",
              "    var cells = IPython.notebook.get_cells();\n",
              "    var ncells = cells.length;\n",
              "    for (var i=0; i<ncells; i++) {\n",
              "        var cell = cells[i];\n",
              "        if (cell.cell_type === 'code'){\n",
              "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
              "                var data = cell.output_area.outputs[j];\n",
              "                if (data.data) {\n",
              "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
              "                    data = data.data;\n",
              "                }\n",
              "                if (data['text/html'] == html_output) {\n",
              "                    return [cell, data, j];\n",
              "                }\n",
              "            }\n",
              "        }\n",
              "    }\n",
              "}\n",
              "\n",
              "// Register the function which deals with the matplotlib target/channel.\n",
              "// The kernel may be null if the page has been refreshed.\n",
              "if (IPython.notebook.kernel != null) {\n",
              "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
              "}\n"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<div id='9c9b2a8f-2dd1-4198-bd10-f0bc4c4a9463'></div>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7fa27eefab50>"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "so6wS1fsIg0k"
      },
      "source": [
        "Most topics have less than 50 reviews.\n",
        "\n",
        "Note that the unassigned cluster has been omitted from the histogram."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qw_rNJNPuXXl"
      },
      "source": [
        "n = len(topic_sizes) - 1 # subtract 1 to ingnore unassigned cluster"
      ],
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vDpuvvfgz5yN"
      },
      "source": [
        "# Visualization of topics\n",
        "\n",
        "This section shows off some of the ways the topics can be visualized with the BERTopic library."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HbfHueiy2v6m",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "35c6a4f8-173c-4259-ba21-fbc7b256347f"
      },
      "source": [
        "# Visualize the 10 topics that are most prevalent in the dataset\n",
        "topic_model.visualize_barchart(top_n_topics=10, \n",
        "                               n_words=5, width=1000, height=800)"
      ],
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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0.014504258500674912], \"xaxis\": \"x8\", \"y\": [\"in  \", \"and  \", \"the  \", \"in charlotte  \", \"charlotte  \"], \"yaxis\": \"y8\"}, {\"marker\": {\"color\": \"#0072B2\"}, \"orientation\": \"h\", \"type\": \"bar\", \"x\": [0.00867199293992911, 0.008712835639857554, 0.009582908396133525, 0.01353174164975244, 0.023663637574409476], \"xaxis\": \"x9\", \"y\": [\"my  \", \"me  \", \"tire  \", \"my car  \", \"car  \"], \"yaxis\": \"y9\"}, {\"marker\": {\"color\": \"#CC79A7\"}, \"orientation\": \"h\", \"type\": \"bar\", \"x\": [0.00705340090245059, 0.007217597136108106, 0.008566199376808413, 0.010312278262095853, 0.014465146563305305], \"xaxis\": \"x10\", \"y\": [\"tacos  \", \"burrito  \", \"taco  \", \"salsa  \", \"mexican  \"], \"yaxis\": \"y10\"}],                        {\"annotations\": [{\"font\": {\"size\": 16}, \"showarrow\": false, \"text\": \"Topic 0\", \"x\": 0.0875, \"xanchor\": \"center\", \"xref\": \"paper\", \"y\": 1.0, \"yanchor\": \"bottom\", \"yref\": \"paper\"}, 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              "                            \n",
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              "        if (!display || display === 'none') {{\n",
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              "            Plotly.purge(gd);\n",
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              "\n",
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              "var notebookContainer = gd.closest('#notebook-container');\n",
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              "</body>\n",
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            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EQz0XACd0-Hg"
      },
      "source": [
        "# Sampling the distribution of topics"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UCWlfzvr7S7P"
      },
      "source": [
        "Let's look at the largest two topics, smallest two topics, and a topic with median."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_7Tg-I9npWZH"
      },
      "source": [
        "def dump_topic_and_docs(text, topic_id):\n",
        "    print(f\"{text} size: {topic_sizes['Count'][topic_id + 1]}\\n\")\n",
        "    n = len(topic_sizes) - 1 \n",
        "\n",
        "    if topic_id != -1:\n",
        "        reviews = topic_model.get_representative_docs(topic_id)\n",
        "        print(\"**** Representative reviews ****\")\n",
        "        for review in reviews:\n",
        "            print(review, \"\\n\")\n",
        "\n",
        "    return topic_model.get_topic(topic_id)[:10]"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uGNgxEPlJjW2"
      },
      "source": [
        "### Unassigned cluster"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "JIo-EPCspue8",
        "outputId": "7997faab-360f-4e6b-c700-fb3c747cfaf2"
      },
      "source": [
        "dump_topic_and_docs(\"Unassigned cluster\", -1)"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Unassigned cluster size: 3115\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('the', 0.006485498038619296),\n",
              " ('and', 0.005975922658815651),\n",
              " ('was', 0.005882849346982429),\n",
              " ('to', 0.005471069304066611),\n",
              " ('it', 0.005163699384497507),\n",
              " ('of', 0.004971711034275305),\n",
              " ('for', 0.004804835025489624),\n",
              " ('is', 0.004672343048500447),\n",
              " ('but', 0.004566944565925044),\n",
              " ('in', 0.004490537388902892)]"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bWz7nBI3KLkF"
      },
      "source": [
        "As we can see, the content of the unassigned cluster contains words that do not strongly belong to any topic."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IE49rFDNwv0F"
      },
      "source": [
        "## Largest topic"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uNGF_JJ4wx2n",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 386
        },
        "outputId": "978c0189-8bdb-4ca8-c540-c66b55c5746b"
      },
      "source": [
        "dump_topic_and_docs(\"Largest topic\", 0)"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Largest topic size: 368\n",
            "\n",
            "**** Representative reviews ****\n",
            "The worst customer service by server and manager. We've been coming here for years. Tonight's experience is one of the worst restaurant experiences I've ever had. Supposedly there was a computer error with our food. Fine, I understand it happens sometimes. However while waiting two hours, we repeatedly asked our server about our dinner. We got the same response every time. \\\"It'll be right up.\\\" He did not\\nconsider actually checking on the food. All the tables around us came, ate and left. Meanwhile, our server could not even remember to bring water to the table without being asked multiple times. \\n\\nAfter I stopped asking nicely about our food, the server finally went to inquire. The manager offered to comp two beers for waiting two hours if we wanted to just  leave. How generous. Otherwise she offered to discount our meals and offered us what we thought was another round of beers. She did not even follow through on that promise. We were given one free beer each. Pathetic. Over 80% of the restaurant was filled with people from our convention. People who make it a point to dine here every time we come. \\n\\nThe server never apologized. Nor did he bother to even clear our plates.\\n\\nThere are plenty of other places to spend your money where it will be appreciated. \n",
            "\n",
            "Went yesterday after my daughter's college graduation.  When the grad ceremony ran longer than expected, I called the hostess to let her know we had been delayed but were departing and hoped to be there soon.  As we were sitting in traffic, I received a call from a man who identified himself as the general manager and rudely asked if I still intended to be dining there.  After I explained our delay and that I had just spoke with the hostess, he (again very rudely) wanted to know how much longer I thought it would take for me to get to the restaurant.  \\n\\nWe arrived at Lydia's about 30 minutes late for a mid-afternoon reservation.   There were several large parties but quite a number of open tables.  Upon presenting at the hostess table, neither the hostess or the general manager acknowledged us for several minutes while they continued some discussion between the two of them.  We were seated at a small round table tucked in a corner - very small for a party of five.\\n\\nOur server arrived and explained the menu, which was the buffet brunch at the time. He spoke so quickly and mumbled so much that we had trouble understanding him.  We ordered our drinks and he indicated he would take our order when he returned with the drinks.  He later returned without our drinks and told us that they needed to break down the buffet to prep for upcoming dinner service so we could not have the antipasto or dessert portions of the brunch. Instead they would charge us ala carte but we would be limited to the entrees on the brunch menu and they could provide a Caesar salad or cup of soup.  He the left and returned later to take our order - still no drinks. \\n\\nWe eventually received Caesar salad (not fresh, limp and overdressed) and drinks.  We were seated within view of the antipasto buffet and were able to observe that we were on to the service of our entrees well before the antipasto buffet was broken down. Clearly there was no reason that our menu needed to be so restricted.  \\n\\nFood was ok.  Chicken was salty and overpowered by capers.  Individuals who ordered pasta trio indicated two of three were good.  Unfortunately, the table set up required the server to hold the pasta skillet over my lap in order to serve those seated on the other side of the table.  No mishaps but a few close calls.  Amounts provided in first serving were small and it was nearly impossible to get an additional serving.  Two individuals never did receive the second serving of one of the pastas that they requested.  We were able to order from dessert menu.  Desserts were unremarkable and very small.  \\n\\nService was horrible.  Our server did not return.  Took great effort to flag him down for additional drinks.  House wine and mimosa were overpriced at $12 and $13 respectively given size and quality.\\n\\nGentleman bussing our table was the only positive of our experience. He was friendly and accommodating.\\n\\nI will not return again and would discourage others as well. \n",
            "\n",
            "After having a sub par meal last night a table that wasn't bolted to the base took a tumble and i ended up at urgent care for stitches.  The owner didn't bother comping our meal ($135) and my MIL had to fight for her to bring it down.  She ended up paying $24. What an insult.  Then, after getting the 8 stitches needed in my ankle, i called to speak with owner and she never called back.  Worst customer experience of my life. \n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('we', 0.009598921317981065),\n",
              " ('our', 0.008503262197735627),\n",
              " ('to', 0.006763928602678122),\n",
              " ('was', 0.006666301867658669),\n",
              " ('the', 0.006375484151262111),\n",
              " ('she', 0.0063215730037490085),\n",
              " ('and', 0.006043346272495334),\n",
              " ('us', 0.005864020564012115),\n",
              " ('he', 0.005237563163380326),\n",
              " ('were', 0.005177237474880569)]"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_sNZ9LYc6PDq"
      },
      "source": [
        "## Smallest topic"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 386
        },
        "id": "6yAuUIIB6cyC",
        "outputId": "dafde19d-9680-4df1-a96b-4533f10a1649"
      },
      "source": [
        "dump_topic_and_docs(\"Smallest topic\", n-1)"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Smallest topic size: 10\n",
            "\n",
            "**** Representative reviews ****\n",
            "Came to this location late at night and was greeted by the friendly staff. Very affordable prices and good food! They even have a dollar menu! I would come back! \n",
            "\n",
            "Not a bad store for a few tough-to-find Middle Eastern items, and the price is right.  Because Labad's doesn't appear to be as popular a destination as other stores in the area, some shelves are scantily stocked, and some items look a bit battered and dusty.  Still, this is the place to go for canned fava beans and Turkish delight.\\n\\nLabad's also offers tasty, filling falafel wraps or gyros for super cheap. \n",
            "\n",
            "This isn't my favorite Showmars, but it does the trick on a busy workday when I need to get in and out with a well priced, non-fast food lunch.  Located just off of South Blvd, parking can be a bit of a squeeze during peak lunch hours, but you'll be able to find a spot behind the restaurant if there isn't one available out front.  \\n\\nToday's lunch of a chicken salad pita with fries and a sweet tea worked just fine.  One thing I do particularly like about this location is the variety of dessert dishes.  In addition to the standard Showmars baklava, they also have several different types of pie (cream and otherwise) - whee! \n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('showmars', 0.03753402813485906),\n",
              " ('pita', 0.029917184491924504),\n",
              " ('love showmars', 0.016653718317785962),\n",
              " ('salad pita', 0.016101654536505094),\n",
              " ('pepperoni rolls', 0.015323628753411958),\n",
              " ('chicken salad', 0.01511593918403704),\n",
              " ('lunch', 0.014480917079336103),\n",
              " ('gyros', 0.011734514740560904),\n",
              " ('599 on', 0.011621235452385106),\n",
              " ('location', 0.011363726138446406)]"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XC59j6wewrCT"
      },
      "source": [
        "## Median size topic"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1XmtgtKNvspr",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 386
        },
        "outputId": "c043ba4d-843c-4ee0-c4ab-d1b55c99b240"
      },
      "source": [
        "dump_topic_and_docs(\"Median topic\", n//2)"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Median topic size: 28\n",
            "\n",
            "**** Representative reviews ****\n",
            "They got some solid subs here, especially on Tuesday for the special.  $6.49 for sub, chips, and a drink.  Just an overall solid place for lunch.  Definitely couldn't handle going here like on a daily, but well worth it to mix things up from time to time.\\n\\ndmo out \n",
            "\n",
            "A neighborhood stalwart and a gem (21 years strong, I am told).  I love this place if no no other reason than meats and cheeses are not sliced until ordered and their staff are not faux \\\"sandwich artists\\\" programmed to put exactly 3 tomato slices and 4 pickles on my six-inch sub.  \\n\\nVeggie friends will love the options here (don't skip the hummus!), but carnivores have the appreciate the fact that there are something like 60 different subs to choose from.  I even love their outmoded ticket system where the cashier has to hit a button on their register to print out what extras you want on your sub.  It's like a flash back to the mid 80s.\\n\\nThough it's at the dead-end of a strip mall that needed an update about 10 years ago, make no mistake that this sub shop is well-loved by the local community.  They have a community board where locals can put up a business card or pictures of their family pets.  If nothing else, this is a perfect distraction while you wait for your sub to be made.  \\n\\nSo yeah, it's a sub shop, much like the dozens you've seen before, but here's a local business that's tied into the community and makes a solidly consistent product.  And oh yeah, free wi-fi! \n",
            "\n",
            "I have been a customer of the Triangle Bar & Grill for over twenty five years.  They have the BEST subs ever. \\n\\nBUT on this trip I was buying several to share with people from out of town.  They are cash only and more than happy to show you an ATM that charges you $2.50 per transaction.  The employees don't set the rules but have to live with them.  That $2.50 came out of their tip, they can hit up their boss for the rest.  Its 2014 and they still don't take credit and or debit cards.  Shame on them. \n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[('sub', 0.038694178547913974),\n",
              " ('subs', 0.012885976977902834),\n",
              " ('subway', 0.011176094579458378),\n",
              " ('mikes', 0.00925778945143283),\n",
              " ('jersey', 0.008382070934593784),\n",
              " ('sub and', 0.008283828260537958),\n",
              " ('jersey mikes', 0.007783925171693379),\n",
              " ('the sub', 0.0076512278358050675),\n",
              " ('cheese', 0.007210145975429207),\n",
              " ('mayo', 0.006687675780528334)]"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    }
  ]
}